Development of Stage-Discharge Relation Using Support Vector Machines

Establishment of rating curves are often required by the hydrologists for flow estimates in the streams, rivers etc. Measurement of discharge in a river is a time-consuming, expensive, and difficult process. Furthermore, the conventional approach of regression analysis of the stage-discharge relation does not provide encouraging results especially during the floods. Therefore, present study is aimed at the application of support vector machines (SVM) based algorithm for modelling stage-discharge relation including the hysteresis effect. A data set of discharge-measuring station located on an Indian river has been used for analysis in the present study. A back propagation neural network model was also employed on the same data in order to compare the performance of the results based on support vector machines based modelling technique. The outcome of the study suggest that the support vector machines works quite well for both the data sets and produced promising results in comparison to the neural network technique. Finally, results also suggest the suitability of SVMs algorithm in predicting the looped rating curve having hysteresis effect as well.